Machine Learning Developer

2 days ago


Bengaluru, India Hirelo Full time

Responsibilities :- Design, develop, and implement machine learning models and algorithms.- Create new models from scratch based on business requirements and data.- Train, fine-tune, and evaluate machine learning models to ensure optimal performance.- Deploy machine learning models into production environments.- Measure and analyse the performance of machine learning models using metrics such as accuracy, precision, recall, F1 score, and ROC-AUC, etc, and iteratively optimise models to meet business objectives.- Conduct performance benchmarking and testing for deployed models, ensuring reliability and scalability in production environments.- Collaborate with cross-functional teams to understand business needs and provide AI/ML solutions.- Optimise and improve the performance of existing models.- Conduct research to identify new methodologies for applying AI/ML within the organisation.- Mentor junior engineers and provide technical guidance.- Stay updated with the latest advancements in AI/ML technologies and methodologies.Requirements :- Machine Learning : Strong understanding of supervised, unsupervised, and reinforcement learning techniques.- Model Development : Experience in developing machine learning models from scratch, including data preprocessing, feature engineering, and model selection.- Deep Learning : Proficiency with deep learning frameworks such as Tensorflow, PyTorch, or Keras.- Natural Language Processing and generation : Experience with NLP techniques and tools, including large language models (LLMs) like GPT, BERT, Llama, etc.- Programming : Proficiency in Python and familiarity with other languages such as Java or C++ is a plus.- Tools and Libraries : Experience with ML libraries and tools such as Scikit-learn, Pandas, NumPy, and SciPy.- Cloud Platforms : Experience with cloud-based ML platforms such as AWS SageMaker, Google Cloud AI, or Azure ML.- MLOps : Knowledge of MLOps practices for model versioning, monitoring, and continuous integration/continuous deployment (CI/CD).- Visualisation : Proficiency with data visualisation tools such as Matplotlib, Seaborn, or Tableau.- Hugging Face : Familiarity with Hugging Face's ecosystem, including the Transformers library for pre-trained models, the datasets library for handling and processing datasets, and the Model Hub for sharing and discovering models.- Prefers folks from Tier 1 colleges. (ref:hirist.tech)



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